Knowledge that Transforms

Using news-based government economic policy uncertainty (EPU) index of Baker et al. (2016) and bank-level data from 17 countries over the period 1998–2012, we find that government economic policy uncertainty has significant positive association with interest rates on bank gross loans. Specifically, a one standard deviation increase in EPU leads to 21.84 basis points increase in average interest rates on bank gross loans. We conjecture the economic policy uncertainty boosts banks’ loan prices by increasing the borrowers’ default risk. The impact of EPU on banks’ loan pricing remains persistent after controlling for banks’ own idiosyncratic default risk and the political risk variables from ICRG database. Results remain robust when we use general elections as an alternative proxy of government economic policy uncertainty. We also confirm main results with syndicated loan deals data and observe a significant positive association between loan spreads and EPU index. Together, our results suggest that government economic policy uncertainty is an economically important risk factor for banks’ loan pricing.

This study investigates how retail payment methods affect aggregate macroeconomic activity. By tracing the relative norms and practices of paper-based payment instruments (checks) and electronic payment methods (payment cards, credit transfers and direct debits) in 27 European Union member countries, the paper reports that a higher penetration ratio of electronic payment methods is generally associated with greater GDP, trade, consumption and tax revenue. The 2008 financial crisis and a country’s shadow economy level have an incremental impact on the relationship between payment methods and economy. The study also finds substitution effects between paper-based and electronic payment methods and complementary effects across electronic payment methods. The findings are robust after controlling for endogeneity. Our study supports policies promoting further repositioning and transfer to efficient electronic payment instruments.

Hjertstrand et al. (2016) recently tested weak separability of the direct utility function using U.S. data on consumption goods, leisure, financial and monetary assets. This paper investigates different forms of weak separability. While weak separability of the direct utility function provides the best fit, by allowing for small errors in the data we find some evidence that financial and monetary assets can be rationalized by a weakly separable indirect utility function. Further we find that M1, a modern analog of money defined by Friedman and Schwartz (1963) and narrow and broader real sector aggregates can be rationalized by indirect weak separability. We also find that M1 and real sector aggregates can be rationalized by homothetic weak separability.

This study attempts to reconcile the conflicting theoretical predictions regarding how government ownership affects bank capital behaviour. Using a unique Chinese bank dataset over 2006–2015 we find that government-owned banks have higher target capital ratios and adjust these ratios faster compared to private banks, supporting the ‘development/political’ view of the government’s role in banking. This effect is stronger for local government-owned and state enterprise-owned banks than for central government-owned banks. We also find that undercapitalized government-owned banks increase equity while undercapitalized foreign banks contract assets and liabilities as their respective main strategy to adjust their capital ratios.

This paper provides evidence of the impact of the new European bank resolution regime on the sovereign-bank nexus. The implementation of the Bank Recovery and Resolution Directive (BRRD) is considered as an exogenous shock which provides the setting for a natural experiment. This investigation tests the financial markets’ perception of the effectiveness of the new rules in weakening the tight interconnectedness between sovereign and bank risk. A Difference-in-Differences (DiD) approach is adopted, building evidence from the Credit Default Swap (CDS) market for banks and non-financial corporates over the period 2011-18. The main findings do not indicate a significant weakening in the interaction between bank and sovereign CDS spreads, compared to the corresponding evidence for the non-financial corporate sector. An overall narrowing of the gap between bank and sovereign risk occurs, which initially implies a lack of credibility of the BRRD in financial markets. However, substantial cross-country variations are identified, particularly for Italy and non-euro area countries. These insights make a significant contribution to the policy debate on effective regulation of the sovereign-bank nexus, in the light of recent developments in the EU post-crisis reform agenda.

We analyze whether bank familiarity affects depositor behavior during financial crisis. Familiarity is measured by regional or local cues in the bank’s name. Depositor behavior is measured by the depositor’s sensitivity to observable bank risk (depositor discipline). Using 2001–2010 bank-level and region-level data for Russia, we find that depositors of familiar banks become less sensitive to bank risk during a financial crisis relative to depositors of unfamiliar banks. To validate that our results stem from a flight to familiarity during crisis and not from implicit guarantees from regional governments, we split our sample along the lines of regional affinity and trust in local governments. The flight to familiarity effect is strongly confirmed in the subsample of regions with strong regional affinity, while the effect is absent in the subsample of regions with more trust in regional and local governments, lending support to the thesis that our results are driven by a flight to familiarity rather than by implicit guarantees.

This paper compares the out-of-sample predictive performance of different early warning models for systemic banking crises using a sample of advanced economies covering the past 45 years. We compare a benchmark logit approach to several machine learning approaches recently proposed in the literature. We find that while machine learning methods often attain a very high in-sample fit, they are outperformed by the logit approach in recursive out-of-sample evaluations. This result is robust to the choice of performance metric, crisis definition, preference parameter, and sample length, as well as to using different sets of variables and data transformations. Thus, our paper suggests that further enhancements to machine learning early warning models are needed before they are able to offer a substantial value-added for predicting systemic banking crises. Conventional logit models appear to use the available information already fairly efficiently, and would for instance have been able to predict the 2007/2008 financial crisis out-of-sample for many countries. In line with economic intuition, these models identify credit expansions, asset price booms and external imbalances as key predictors of systemic banking crises.

Following up on claims that high and rising levels of financial inclusion might contribute to financial stability, we test whether level and progress in financial inclusion has an effect on the magnitude of a financial bust after a crisis. We do this for the global financial crisis and a sample of crisis episodes covering the period 2004–2017. We find some evidence that countries with more inclusive banking sectors show less pronounced credit busts in times of financial turbulence. However, higher borrower growth rates in the years preceding a crisis have no mitigating effect on the depth of the bust. Thus, it remains a policy challenge to expand financial inclusion without contributing a potentially destabilizing credit boom.

The recent experience during the debt and banking crises in the European Monetary Union (EMU) has demonstrated how important it is to consider liquidity (or rather the lack thereof) in macroeconomics. Similar to the Fed's policy during the US real estate crisis, the ECB took huge efforts to insert liquidity into the banking sector to prevent further financial turmoil, only to find that the transmission mechanism was severely hampered. Strong heterogeneity during the crises accentuated the difficulties of a common monetary policy. The main contribution of this paper is to show that properly measured liquidity contains substantial information on macroeconomic dynamics. Liquidity overcomes two problems of using interest rates (and interest rate spreads) as the main indicator of the monetary and financial side of the economy. First, contrary to the policy rate, they include information on the different impacts of monetary shocks between countries, thereby accounting for heterogeneity in the transmission mechanism and the different states of the banking sector. Second, (growth rates of) liquidity indicators are not subject to the zero lower bound problem and are thus particularly useful when considering samples, such as the recent crisis. We propose a range of liquidity indicators, based on Theil-Törnqvist index number, that are designed to account for measurement problems during times of financial turmoil, when liquidity preference – and thus the price of liquidity – can change quickly. We then study the information content of those variables.